Abstract
In this paper, we propose a new class of continuous distributions with two extra shape parameters called the a new type I half logistic-G family of distributions. Some of important properties including ordinary moments, quantiles, moment generating function, mean deviation, moment of residual life, moment of reversed residual life, order statistics and extreme value are obtained. To estimate the model parameters, the maximum likelihood method is also applied by means of Monte Carlo simulation study. A new location-scale regression model based on the new type I half logistic-Weibull distribution is then introduced. Applications of the proposed family is demonstrated in many fields such as survival analysis and univariate data fitting. Empirical results show that the proposed models provide better fits than other well-known classes of distributions in many application fields.
Highlights
The essential limitations and problems of the classic statistical distributions in data modelling lead statistical researcher to introduce new flexible distributions
The readers are referred to Marshall-Olkin generated (MO-G) by Marshall and Olkin [16], Odd log-logistic-G by Gleaton and Lynch [12], Kumaraswamy-G (Kw-G) by Cordeiro and de Castro [7], McDonald-G (Mc-G) by Alexander et al [1], Weibull-G by Bourguignon et al [6], exponentiated half-logistic by Cordeiro et al [10], transformer (T-X) by Alzaatreh et al [2], Lomax generator by Cordeiro et al [14], Kumaraswamy Marshal-Olkin family by Alizadeh et al [3], Beta Marshal-OLkin family by Alizadeh et al [4], and type I half-logistic family by Cordeiro et al [11] to see some of the most important distributions with required flexibilities to apply a wide range of data sets
In this paper, using T-X idea proposed by Alzaatreh et al [2] and Odd log-logistic-G by Gleaton and Lynch [12], we introduce a new family of distributions
Summary
The essential limitations and problems of the classic statistical distributions in data modelling lead statistical researcher to introduce new flexible distributions. These new distributions are often made through the classic distributions and provide the necessary flexibilities with respect to the classic distributions. In this paper, using T-X idea proposed by Alzaatreh et al [2] and Odd log-logistic-G by Gleaton and Lynch [12], we introduce a new family of distributions. The NT1HL-G family provides a new possibility to model these kind of data sets. A STUDY ON A NEW TYPE 1 HALF-LOGISTIC FAMILY OF DISTRIBUTIONS AND ITS APPLICATIONS
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
